{"id":"W4413415478","doi":"10.2196/75279","title":"Leveraging Retrieval-Augmented Large Language Models for Dietary Recommendations With Traditional Chinese Medicine’s Medicine Food Homology: Algorithm Development and Validation","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Traditional Chinese Medicine Studies","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Southeast University; National Natural Science Foundation of China","keywords":"Computer science; Precision medicine; Traditional Chinese medicine; Algorithm; Artificial intelligence; Natural language processing; Medicine; Alternative medicine; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002715133,0.001243928,0.0009529631,0.001617179,0.0005990273,0.001444015,0.001885754,0.001641655,0.003129232],"category_scores_gemma":[0.01052372,0.0005432781,0.001652178,0.00107383,0.0005221083,0.001721769,0.00154059,0.002017231,0.001106358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001226808,"about_ca_system_score_gemma":0.002426672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01885723,"about_ca_topic_score_gemma":0.02250435,"domain_scores_codex":[0.9989814,0.0004257796,0.00008344285,0.0002708537,0.0001578574,0.00008053309],"domain_scores_gemma":[0.9942861,0.004721757,0.0001708066,0.000292014,0.0004496065,0.00007975123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004321251,0.0004179468,0.006655599,0.0004763914,0.0003541668,0.0004131525,0.0003028745,0.47249,0.004213005,0.006643626,0.007995078,0.499606],"study_design_scores_gemma":[0.00002896543,0.00002827368,0.000206803,0.00001209236,0.00002751689,0.00003208248,0.00003431342,0.9960502,0.0005836303,0.002347987,0.0006412701,0.000006872298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08333277,0.001664691,0.8979779,0.001177161,0.0001243128,0.0007234392,0.001288846,0.01113041,0.002580534],"genre_scores_gemma":[0.3534148,0.0004550977,0.6393012,0.0005682053,0.00007542296,0.0005799315,0.003653805,0.0002709096,0.001680589],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01885723,"threshold_uncertainty_score":0.03749496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04443141074045245,"score_gpt":0.3301811419147976,"score_spread":0.2857497311743452,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}